Malware protection for virtual machines

ABSTRACT

A computer-implemented method at a data management system comprises: receiving, at a storage appliance from a server hosting a virtual machine, a write made to the virtual machine; computing, at the storage appliance, a fingerprint of the transmitted write; comparing, at the storage appliance, the computed fingerprint to malware fingerprints in a malware catalog; repeating the computing and comparing; and disabling the virtual machine if a number of matches from the comparing breaches a predetermined threshold over a predetermined amount of time.

TECHNICAL FIELD

The present disclosure generally relates to virtual machines and moreparticularly, but not exclusively, to malware protection for virtualmachines.

BACKGROUND

Malware, or malicious software, is software intentionally designed tocause damage to a computing device or act against the interest of theuser of the computing device. Malware can include spyware, ransomware,viruses, etc. A virtual machine, which is an emulation of a computingdevice, can also be subject to malware.

BRIEF DESCRIPTION OF THE DRAWINGS

To more easily identify the discussion of any particular element or act,the most significant digit or digits in a reference number refer to thefigure (“FIG.”) number in which that element or act is first introduced.

FIG. 1A depicts a networked computing environment in which the disclosedtechnology may be practiced, according to some example embodiments.

FIG. 1B depicts a server of a networked computing environment, accordingto some example embodiments.

FIG. 1C depicts a storage appliance of a networked computingenvironment, according to some example embodiments.

FIG. 2 shows an example virtualized infrastructure manager.

FIG. 3 shows an example method for protecting a virtual machine frommalware.

FIG. 4 shows an example workload management system.

FIG. 5 shows an example flow diagram of restoring a virtual machine.

FIG. 6 is a block diagram illustrating a representative softwarearchitecture, which may be used in conjunction with various hardwarearchitectures herein described.

FIG. 7 is a block diagram illustrating components of a machine,according to some example embodiments, able to read instructions from amachine-readable medium (e.g., a machine-readable storage medium) andperform any one or more of the methodologies discussed herein.

DETAILED DESCRIPTION

The description that follows includes systems, methods, techniques,instruction sequences, and computing machine program products thatembody illustrative embodiments of the disclosure. In the followingdescription, for the purposes of explanation, numerous specific detailsare set forth in order to provide an understanding of variousembodiments of the inventive subject matter. It will be evident,however, to those skilled in the art, that embodiments of the inventivesubject matter may be practiced without these specific details. Ingeneral, well-known instruction instances, protocols, structures, andtechniques are not necessarily shown in detail.

Embodiments provide real-time protection against malware for virtualmachines. In an embodiment, a filter driver is installed in virtualizedinfrastructure managers. The filter driver streams writes done in thevirtual machine in real time to a cluster. The cluster can monitor thesewrites and look for malicious software being downloaded in all the VMsbeing protected.

FIG. 1A depicts one embodiment of a networked computing environment 100in which the disclosed technology may be practiced. As depicted, thenetworked computing environment 100 includes a datacenter 150, a storageappliance 140, and a computing device 154 in communication with eachother via one or more networks 180. The networked computing environment100 may include a plurality of computing devices interconnected throughone or more networks 180. The one or more networks 180 may allowcomputing devices and/or storage devices to connect to and communicatewith other computing devices and/or other storage devices. In somecases, the networked computing environment 100 may include othercomputing devices and/or other storage devices not shown. The othercomputing devices may include, for example, a mobile computing device, anon-mobile computing device, a server, a work station, a laptopcomputer, a tablet computer, a desktop computer, or an informationprocessing system. The other storage devices may include, for example, astorage area network storage device, a networked-attached storagedevice, a hard disk drive, a solid-state drive, or a data storagesystem.

The datacenter 150 may include one or more servers, such as server 160,in communication with one or more storage devices, such as storagedevice 156. The one or more servers may also be in communication withone or more storage appliances, such as storage appliance 170. Theserver 160, storage device 156, and storage appliance 170 may be incommunication with each other via a networking fabric connecting serversand data storage units within the datacenter 150 to each other. Thestorage appliance 170 may include a data management system for backingup virtual machines and/or files within a virtualized infrastructure.The server 160 may be used to create and manage one or more virtualmachines associated with a virtualized infrastructure.

The one or more virtual machines may run various applications, such as adatabase application or a web server (e.g., a web server hosting anauto-parts website). The storage device 156 may include one or morehardware storage devices for storing data, such as a hard disk drive(HDD), a magnetic tape drive, a solid-state drive (SSD), a storage areanetwork (SAN) storage device, or a networked attached storage (NAS)device. In some cases, a datacenter, such as datacenter 150, may includethousands of servers and/or data storage devices in communication witheach other. The data storage devices may comprise a tiered data storageinfrastructure (or a portion of a tiered data storage infrastructure).The tiered data storage infrastructure may allow for the movement ofdata across different tiers of a data storage infrastructure betweenhigher-cost, higher-performance storage devices (e.g., solid-statedrives and hard disk drives) and relatively lower-cost,lower-performance storage devices (e.g., magnetic tape drives).

The one or more networks 180 may include a secure network such as anenterprise private network, an unsecure network such as a wireless opennetwork, a local area network (LAN), a wide area network (WAN), and theInternet. The one or more networks 180 may include a cellular network, amobile network, a wireless network, or a wired network. Each network ofthe one or more networks 180 may include hubs, bridges, routers,switches, and wired transmission media such as a direct-wiredconnection. The one or more networks 180 may include an extranet orother private network for securely sharing information or providingcontrolled access to applications or files.

A server, such as server 160, may allow a client to download informationor files (e.g., executable, text, application, audio, image, or videofiles) from the server 160 or to perform a search query related toparticular information stored on the server 160. In some cases, a servermay act as an application server or a file server. In general, a servermay refer to a hardware device that acts as the host in a client-serverrelationship or a software process that shares a resource with orperforms work for one or more clients.

One embodiment of server 160 includes a network interface 165, processor166, memory 167, disk 168, and virtualization manager 169 all incommunication with each other. Network interface 165 allows server 160to connect to one or more networks 180. Network interface 165 mayinclude a wireless network interface and/or a wired network interface.Processor 166 allows server 160 to execute computer-readableinstructions stored in memory 167 in order to perform processesdescribed herein. Processor 166 may include one or more processingunits, such as one or more CPUs and/or one or more GPUs. Memory 167 maycomprise one or more types of memory (e.g., RAM, SRAM, DRAM, ROM,EEPROM, Flash, etc.). Disk 168 may include a hard disk drive and/or asolid-state drive. Memory 167 and disk 168 may comprise hardware storagedevices.

The virtualization manager 169 may manage a virtualized infrastructureand perform management operations associated with the virtualizedinfrastructure. The virtualization manager 169 may manage theprovisioning of virtual machines running within the virtualizedinfrastructure and provide an interface to computing devices interactingwith the virtualized infrastructure. In one example, the virtualizationmanager 169 may set a virtual machine into a frozen state in response toa snapshot request made via an application programming interface (API)by a storage appliance (e.g., agent installed on the storage appliance),such as storage appliance 140 or storage appliance 170. Setting thevirtual machine into a frozen state may allow a point-in-time snapshotof the virtual machine to be stored or transferred. In one example,updates made to a virtual machine that has been set into a frozen statemay be written to a separate file (e.g., an update file) while thevirtual machine may be set into a read-only state to preventmodifications to the virtual disk file while the virtual machine is inthe frozen state.

The virtualization manager 169 may then transfer data associated withthe virtual machine (e.g., an image of the virtual machine or a portionof the image of the virtual disk file associated with the state of thevirtual disk at a point in time is frozen) to a storage appliance inresponse to a request made by the storage appliance 170. After the dataassociated with the point-in-time snapshot of the virtual machine hasbeen transferred to the storage appliance 170, the virtual machine maybe released from the frozen state (i.e., unfrozen) and the updates madeto the virtual machine and stored in the separate file may be mergedinto the virtual disk file. The virtualization manager 169 may performvarious virtual machine-related tasks, such as cloning virtual machines,creating new virtual machines, monitoring the state of virtual machines,moving virtual machines between physical hosts for load balancingpurposes, and facilitating backups of virtual machines.

One embodiment of storage appliance 170 includes a network interface175, processor 176, memory 177, and disk 178 all in communication witheach other. Network interface 175 allows storage appliance 170 toconnect to one or more networks 180. Network interface 175 may include awireless network interface and/or a wired network interface. Processor176 allows storage appliance 170 to execute computer-readableinstructions stored in memory 177 in order to perform processesdescribed herein. Processor 176 may include one or more processingunits, such as one or more CPUs and/or one or more GPUs. Memory 177 maycomprise one or more types of memory (e.g., RAM, SRAM, DRAM, ROM,EEPROM, NOR Flash, NAND Flash, etc.). Disk 178 may include a hard diskdrive and/or a solid-state drive. Memory 177 and disk 178 may comprisehardware storage devices.

In one embodiment, the storage appliance 170 may include four machines.Each of the four machines may include a multi-core CPU, 64 GB of RAM, a400 GB SSD, three 4 TB HDDs, and a network interface controller. In thiscase, the four machines may be in communication with the one or morenetworks 180 via the four network interface controllers. The fourmachines may comprise four nodes of a server cluster. The server clustermay comprise a set of physical machines that are connected together viaa network. The server cluster may be used for storing data associatedwith a plurality of virtual machines, such as backup data associatedwith different point-in-time versions of thousands of virtual machines.

The networked computing environment 100 may provide a cloud computingenvironment for one or more computing devices. Cloud computing may referto Internet-based computing, wherein shared resources, software, and/orinformation may be provided to one or more computing devices on-demandvia the Internet. The networked computing environment 100 may comprise acloud computing environment providing Software-as-a-Service (SaaS) orInfrastructure as-a-Service (IaaS) services, SaaS may refer to asoftware distribution model in which applications are hosted by aservice provider and made available to end users over the Internet. Inone embodiment, the networked computing environment 100 may include avirtualized infrastructure that provides software, data processing,and/or data storage services to end users accessing the services via thenetworked computing environment 100. In one example, networked computingenvironment 100 may provide cloud-based work productivity orbusiness-related applications to a computing device, such as computingdevice 154.

The storage appliance 140 may comprise a cloud-based data managementsystem for backing up virtual machines and/or files within a virtualizedinfrastructure, such as virtual machines running on server 160 or filesstored on server 160 (e.g., locally stored files, files stored inmounted directories), according to some example embodiments.

In some cases, networked computing environment 100 may provide remoteaccess to secure applications and files stored within datacenter 150from a remote computing device, such as computing device 154. Thedatacenter 150 may use an access control application to manage remoteaccess to protected resources, such as protected applications,databases, or files located within the datacenter 150. To facilitateremote access to secure applications and files, a secure networkconnection may be established using a virtual private network (VPN). AVPN connection may allow a remote computing device, such as computingdevice 154, to securely access data from a private network (e.g., from acompany file server or mail server) using an unsecure public network orthe Internet, The VPN connection may require client-side software (e.g.,running on the remote computing device) to establish and maintain theVPN connection. The VPN client software may provide data encryption andencapsulation prior to the transmission of secure private networktraffic through the Internet.

In some embodiments, the storage appliance 170 may manage the extractionand storage of virtual machine snapshots associated with differentpoint-in-time versions of one or more virtual machines running withinthe datacenter 150. A snapshot of a virtual machine may correspond witha state of the virtual machine at a particular point in time. Inresponse to a restore command from the server 160, the storage appliance170 may restore a point-in-time version of a virtual machine or restorepoint-in-time versions of one or more files located on the virtualmachine and transmit the restored data to the server 160. in response toa mount command from the server 60, the storage appliance 170 may allowa point-in-time version of a virtual machine to be mounted and allow theserver 160 to read and/or modify data associated with the point-in-timeversion of the virtual machine. To improve storage density, the storageappliance 170 may deduplicate and compress data associated withdifferent versions of a virtual machine and/or deduplicate and compressdata associated with different virtual machines. To improve systemperformance, the storage appliance 170 may first store virtual machinesnapshots received from a virtualized environment in a cache, such as aflash-based cache. The cache may also store popular data or frequentlyaccessed data (e.g., based on a history of virtual machine restorations,incremental files associated with commonly restored virtual machineversions) and current day incremental files or incremental filescorresponding with snapshots captured within the past 24 hours.

An incremental file may comprise a forward incremental file or a reverseincremental file. A forward incremental file may include a set of datarepresenting changes that have occurred since an earlier point-in-timesnapshot of a virtual machine. To generate a snapshot of the virtualmachine corresponding with a forward incremental file, the forwardincremental file may be combined with an earlier point-in-time snapshotof the virtual machine (e.g., the forward incremental file may becombined with the last full image of the virtual machine that wascaptured before the forward incremental file was captured and any otherforward incremental files that were captured subsequent to the last fullimage and prior to the forward incremental file). A reverse incrementalfile may include a set of data representing changes from a laterpoint-in-time snapshot of a virtual machine. To generate a snapshot ofthe virtual machine corresponding with a reverse incremental file, thereverse incremental file may be combined with a later point-in-timesnapshot of the virtual machine (e.g., the reverse incremental file maybe combined with the most recent snapshot of the virtual machine and anyother reverse incremental files that were captured prior to the mostrecent snapshot and subsequent to the reverse incremental file).

The storage appliance 170 may provide a user interface (e.g., aweb-based interface or a graphical user interlace) that displays virtualmachine backup information such as identifications of the virtualmachines protected and the historical versions or time machine views foreach of the virtual machines protected. A time machine view of a virtualmachine may include snapshots of the virtual machine over a plurality ofpoints in time. Each snapshot may comprise the state of the virtualmachine at a particular point in time. Each snapshot may correspond witha different version of the virtual machine (e.g., Version 1 of a virtualmachine may correspond with the state of the virtual machine at a firstpoint in time and Version 2 of the virtual machine may correspond withthe state of the virtual machine at a second point in time subsequent tothe first point in time).

The user interface may enable an end user of the storage appliance 170(e.g., a system administrator or a virtualization administrator) toselect a particular version of a virtual machine to be restored ormounted. When a particular version of a virtual machine has beenmounted, the particular version may be accessed by a client (e,g., avirtual machine, a physical machine, or a computing device) as if theparticular version was local to the client. A mounted version of avirtual machine may correspond with a mount point directory (e.g.,/snapshots/VM5Nersion23). In one example, the storage appliance 170 mayrun an NFS server and make the particular version (or a copy of theparticular version) of the virtual machine accessible for reading and/orwriting. A user (e.g., database administrator) of the storage appliance170 may then select the particular version to be mounted and run anapplication (e.g., a data analytics application) using the mountedversion of the virtual machine. In another example, the particularversion may be mounted as an iSCSI target.

In some example embodiments, the storage appliance 140 is an externalnetwork connected database appliance comprising an agent 142, anapplication 144, and a storage device 146. In some example embodiments,the application 144 is a database application for managing a database(e.g., Oracle database management system) that can store database datalocally on the storage device 146, or on remote storage locations, suchas within the datacenter 150. The agent 142 is a remote connectionsystem for performing snapshots of database data (e.g., application144), and can further implement bootstrapping, upgrade, and furtherinclude backup features to transfer data from the storage appliance 140to datacenter 150 via networks 180.

In some example embodiments, the agent 142 can be uploaded from thedatacenter 150 and installed on the storage appliance 140. Afterinstallation on storage appliance 140, the agent 142 can be enabled ordisabled by the storage appliance 140 over time. The agent 142 mayacquire one or more electronic files or snapshot information associatedwith the one or more electronic files from the application 144. Thesnapshot information may include full and/or differential snapshot data.In one example, the one or more electronic files may comprise a databasefile for a database and the snapshot information may comprise adifferential backup of the database file.

In those embodiments in which the application 144 is a databaseapplication that manages a database, the agent 142 is configured toacquire one or more electronic files corresponding with a firstpoint-in-time version of the database from the database application. Theagent 142 can further acquire a database file for the database from theapplication 144 or acquire a full or differential backup of the databasefrom the computing application 144. The determination of whether theagent 142 acquires the database file or the full or differential backupmay depend on a file size of the database file. The database file maycomprise a text file or a binary file. The agent 142 may transfer one ormore changed data blocks corresponding with the first point-in-timeversion of the database to the storage appliance 140. The one or morechanged data blocks may be identified by the agent 142 by generating andcomparing fingerprints or signatures for data blocks of the databasefile with previously generated fingerprints or signatures associatedwith earlier point-in-time versions of the database file captured priorto the first point in time. In some example embodiments, the agent 142can perform automatic upgrades or downgrades the backup agent 142 to bein-sync with software changes to a plurality of nodes (e.g., nodesoperating within storage appliance 170).

In some example embodiments, the agent 142 is further configured tointerface with application 144 or storage device 146 to implementchanges, such as creating directories, database instances, reads/writes,and other operations to provide database management functions betweenthe storage appliance 140 and devices within datacenter 150. Forexample, the application 144 can be a relational database managementapplication with plugin functionality, in which third-party developedplugins or extensions can be integrated in the application 144 toperform actions, such as creation of a database instance.

FIG. 1B depicts one embodiment of server 160 in FIG. 1A. The server 160may comprise one server out of a plurality of servers that are networkedtogether within a datacenter 150. In one example, the plurality ofservers may be positioned within one or more server racks within thedatacenter 150. As depicted, the server 160 includes hardware-levelcomponents and software-level components. The hardware-level componentsinclude one or more processors 182, one or more memory 184, and one ormore disks 185. The software-level components include a hypervisor 186,a virtualized infrastructure manager 199, and one or more virtualmachines, such as virtual machine 198. The hypervisor 186 may comprise anative hypervisor or a hosted hypervisor. The hypervisor 186 may providea virtual operating platform for running one or more virtual machines,such as virtual machine 198. Virtual machine 198 includes a plurality ofvirtual hardware devices including a virtual processor 192, a virtualmemory 194, and a virtual disk 195. The virtual disk 195 may comprise afile stored within the one or more disks 185. In one example, a virtualmachine may include a plurality of virtual disks, with each virtual diskof the plurality of virtual disks associated with a different filestored on the one or more disks 185. Virtual machine 198 may include aguest operating system 196 that runs one or more applications, such asapplication 197.

The virtualized infrastructure manager 199, which may correspond withthe virtualization manager 169 in FIG. 1A, may run on a virtual machineor natively on the server 160. The virtualized infrastructure manager199 may provide a centralized platform for managing a virtualizedinfrastructure that includes a plurality of virtual machines. Thevirtualized infrastructure manager 199 may manage the provisioning ofvirtual machines running within the virtualized infrastructure andprovide an interface to computing devices interacting with thevirtualized infrastructure. The virtualized infrastructure manager 199may perform various virtualized infrastructure-related tasks, such ascloning virtual machines, creating new virtual machines (e.g., newvirtual machines for new nodes of the cluster), monitoring the state ofvirtual machines, and facilitating backups of virtual machines.

In one embodiment, the server 160 may use the virtualized infrastructuremanager 199 to facilitate backups for a plurality of virtual machines(e.g., eight different virtual machines) running on the server 160. Eachvirtual machine running on the server 160 may run its own guestoperating system and its own set of applications. Each virtual machinerunning on the server 160 may store its own set of files using one ormore virtual disks associated with the virtual machine (e.g., eachvirtual machine may include two virtual disks that are used for storingdata associated with the virtual machine).

In one embodiment, a data management application running on a. storageappliance, such as storage appliance 140 in FIG. 1A or storage appliance170 in FIG. 1A, may request a snapshot of a virtual machine running onserver 160. The snapshot of the virtual machine may be stored as one ormore files, with each file associated with a virtual disk of the virtualmachine. A snapshot of a virtual machine may correspond with a state ofthe virtual machine at a particular point in time. The particular pointin time may be associated with a time stamp. In one example, a firstsnapshot of a virtual machine may correspond with a first state of thevirtual machine (including the state of applications and files stored onthe virtual machine) at a first point in time and a second snapshot ofthe virtual machine may correspond with a second state of the virtualmachine at a second point in time subsequent to the first point in time.

In response to a request for a snapshot of a virtual machine at aparticular point in time, the virtualized infrastructure manager 199 mayset the virtual machine into a frozen state or store a copy of thevirtual machine at the particular point in time. The virtualizedinfrastructure manager 199 may then transfer data associated with thevirtual machine (e.g., an image of the virtual machine or a portion ofthe image of the virtual machine) to the storage appliance. The dataassociated with the virtual machine may include a set of files includinga virtual disk file storing contents of a virtual disk of the virtualmachine at the particular point in time and a virtual machineconfiguration file storing configuration settings for the virtualmachine at the particular point in time. The contents of the virtualdisk file may include the operating system used by the virtual machine,local applications stored on the virtual disk, and user files (e.g.,images and word processing documents). In some cases, the virtualizedinfrastructure manager 199 may transfer a full image of the virtualmachine to the storage appliance or a plurality of data blockscorresponding with the full image (e.g., to enable a full image-levelbackup of the virtual machine to be stored on the storage appliance). Inother cases, the virtualized infrastructure manager 199 may transfer aportion of an image of the virtual machine associated with data that haschanged since an earlier point in time prior to the particular point intime or since a last snapshot of the virtual machine was taken. In oneexample, the virtualized infrastructure manager 199 may transfer onlydata associated with virtual blocks stored on a virtual disk of thevirtual machine that have changed since the last snapshot of the virtualmachine was taken. In one embodiment, the data management applicationmay specify a first point in time and a second point in time and thevirtualized infrastructure manager 199 may output one or more virtualdata blocks associated with the virtual machine that have been modifiedbetween the first point in time and the second point in time.

In some embodiments, the server 160 or the hypervisor 186 maycommunicate with a storage appliance, such as storage appliance 140 inFIG. 1A or storage appliance 170 in FIG. 1A, using a distributed filesystem protocol such as Network File System (NFS) Version 3. Thedistributed file system protocol may allow the server 160 or thehypervisor 186 to access, read, write, or modify files stored on thestorage appliance as if the files were locally stored on the server 160.The distributed file system protocol may allow the server 160 or thehypervisor 186 to mount a directory or a portion of a file systemlocated within the storage appliance 140. For example, the storageappliance 140 can include a standalone host of a database, where theserver 160 mounts the database directories as if the files were locallystored on server 160. Further, the server 160 may function as a backupdevice for storage appliance 140 by backing up data in the mounteddirectories in a distributed database within the datacenter 150, such asa cluster of nodes in the storage appliance 170.

FIG. 1C depicts one embodiment of the storage appliance 170 in FIG, 1A.The storage appliance 170 may include a plurality of physical machinesthat may be grouped together and presented as a single computing system.Each physical machine of the plurality of physical machines may comprisea node in a cluster (e.g., a failover cluster, a Cassandra cluster). Inone example, the storage appliance 170 may be positioned within a serverrack within a datacenter. As depicted, the storage appliance 170includes hardware-level components and software-level components. Thehardware-level components include one or more physical machines, such asphysical machine 120 and physical machine 130. The physical machine 120includes a network interface 121, processor 122, memory 123, and disk124 all in communication with each other. Processor 122 allows physicalmachine 120 to execute computer-readable instructions stored in memory123 to perform processes described herein. Disk 124 may include a harddisk drive and/or a solid-state drive. The physical machine 130 includesa network interface 131, processor 132, memory 133, and disk 134 all incommunication with each other. Processor 132 allows physical machine 130to execute computer-readable instructions stored in memory 133 toperform processes described herein. Disk 134 may include a hard diskdrive and/or a solid-state drive. In some cases, disk 134 may include aflash-based SSD or a hybrid HDD/SSD drive. In one embodiment, thestorage appliance 170 may include a plurality of physical machinesarranged in a cluster (e.g., four machines in a cluster). Each of theplurality of physical machines may include a plurality of multi-coreCPUs, 128 GB of RAM, a 500 GB SSD, four 4 TB HDDs, and a networkinterface controller.

In some embodiments, the plurality of physical machines may be used toimplement a cluster-based network fileserver. The cluster-based networkfile server may neither require nor use a front-end load balancer. Oneissue with using a front-end load balancer to host the IP address forthe cluster-based network file server and to forward requests to thenodes of the cluster-based network file server is that the front-endload balancer comprises a single point of failure for the cluster-basednetwork file server. In some cases, the file system protocol used by aserver, such as server 160 in FIG. 1A, or a hypervisor, such ashypervisor 186 in FIG. 1B, to communicate with the storage appliance 170may not provide a failover mechanism (e.g., NFS Version 3). In the casethat no failover mechanism is provided on the client side, thehypervisor may not be able to connect to a new node within a cluster inthe event that the node connected to the hypervisor fails.

In some embodiments, each node in a cluster may be connected to eachother via a network and may be associated with one or more IP addresses(e.g., two different IP addresses may be assigned to each node). In oneexample, each node in the cluster may be assigned a permanent IP addressand a floating IP address and may be accessed using either the permanentIP address or the floating IP address. In this case, a hypervisor, suchas hypervisor 186 in FIG. 1B, may be configured with a first floating IPaddress associated with a first node in the cluster. The hypervisor 186may connect to the cluster using the first floating IP address. In oneexample, the hypervisor 186 may communicate with the cluster using theNFS Version 3 protocol. Each node in the cluster may run a VirtualRouter Redundancy Protocol (VRRP) daemon. A daemon may comprise abackground process. Each VRRP daemon may include a list of all floatingIP addresses available within the cluster. In the event that the firstnode associated with the first floating IP address fails, one of theVRRP daemons may automatically assume or pick up the first floating IPaddress if no other VRRP daemon has already assumed the first floatingIP address. Therefore, if the first node in the cluster fails orotherwise goes down, then one of the remaining VRRP daemons running onthe other nodes in the cluster may assume the first floating IP addressthat is used by the hypervisor 186 for communicating with the cluster.

In order to determine which of the other nodes in the cluster willassume the first floating IP address, a VRRP priority may beestablished. In one example, given a number (N) of nodes in a clusterfrom node(0) to node(N−1), for a floating IP address (i), the VRRPpriority of nodeG) may be G-i) modulo N. In another example, given anumber (N) of nodes in a cluster from node(0) to node(N−1), for afloating IP address (i), the VRRP priority of nodeG) may be (i-j) moduloN. In these cases, nodeG) will assume floating IP address (i) only ifits VRRP priority is higher than that of any other node in the clusterthat is alive and announcing itself on the network. Thus, if a nodefails, then there may be a clear priority ordering for determining whichother node in the cluster will take over the failed node's floating IPaddress.

In some cases, a cluster may include a plurality of nodes and each nodeof the plurality of nodes may be assigned a different floating IPaddress. In this case, a first hypervisor may be configured with a firstfloating IP address associated with a first node in the cluster, asecond hypervisor may be configured with a second floating IP addressassociated with a second node in the cluster, and a third hypervisor maybe configured with a third floating IP address associated with a thirdnode in the cluster.

As depicted in FIG. 1C, the software-level components of the storageappliance 170 may include data management system 102, a virtualizationinterface 104, a distributed job scheduler 108, a distributed metadatastore 110, a distributed file system 112, and one or more virtualmachine search indexes, such as virtual machine search index 106. In oneembodiment, the software-level components of the storage appliance 170may be run using a dedicated hardware-based appliance. In anotherembodiment, the software-level components of the storage appliance 170may be run from the cloud (e.g., the software-level components may beinstalled on a cloud service provider).

In some cases, the data storage across a plurality of nodes in a cluster(e.g., the data storage available from the one or more physicalmachines) may be aggregated and made available over a single file systemnamespace (e.g., /snap-50 shots/). A directory for each virtual machineprotected using the storage appliance 170 may be created (e.g., thedirectory for Virtual Machine A may be /snapshots/VM_A). Snapshots andother data associated with a virtual machine may reside within thedirectory for the virtual machine. In one example, snapshots of avirtual machine may be stored in subdirectories of the directory (e.g.,a first snapshot of Virtual Machine A may reside in /snapshots/VM_A/s1/and a second snapshot of Virtual Machine A may reside in/snapshots/VM_A/s2/).

The distributed file system 112 may present itself as a single filesystem, in which, as new physical machines or nodes are added to thestorage appliance 170, the cluster may automatically discover theadditional nodes and automatically increase the available capacity ofthe file system 112 for storing files and other data. Each file storedin the distributed file system 112 may be partitioned into one or morechunks or shards. Each of the one or more chunks may be stored withinthe distributed file system 112 as a separate file. The files storedwithin the distributed file system 112 may be replicated or mirroredover a plurality of physical machines, thereby creating a load-balancedand fault-tolerant distributed file system 112. In one example, storageappliance 170 may include ten physical machines arranged as a failovercluster and a first file corresponding with a snapshot of a virtualmachine (e.g., /snapshots/VM_A/s1/s1.full) may be replicated and storedon three of the ten machines.

The distributed metadata store 110 may include a distributed databasemanagement system that provides high availability without a single pointof failure. In one embodiment, the distributed metadata store 110 maycomprise a database, such as a distributed document-oriented database.The distributed metadata store 110 may be used as a distributed keyvalue storage system. In one example, the distributed metadata store 110may comprise a distributed NoSQL key value store database. In somecases, the distributed metadata store 110 may include a partitioned rowstore, in which rows are organized into tables or other collections ofrelated data held within a structured format within the key value storedatabase. A table (or a set of tables) may be used to store metadatainformation associated with one or more files stored within thedistributed file system 112. The metadata information may include thename of a file, a size of the file, file permissions associated with thefile, when the file was last modified, and file mapping informationassociated with an identification of the location of the file storedwithin a cluster of physical machines. In one embodiment, a new filecorresponding with a snapshot of a virtual machine may be stored withinthe distributed file system 112 and metadata associated with the newfile may be stored within the distributed metadata store 110 Thedistributed metadata store 110 may also be used to store a backupschedule for the virtual machine and a list of snapshots for the virtualmachine that are stored using the storage appliance 170.

In some cases, the distributed metadata store 110 may be used to manageone or more versions of a virtual machine. Each version of the virtualmachine may correspond with a full image snapshot of the virtual machinestored within the distributed file system 112 or an incremental snapshotof the virtual machine (e.g., a forward incremental or reverseincremental) stored within the distributed file system 112. In oneembodiment, the one or more versions of the virtual machine maycorrespond with a plurality of files. The plurality of files may includea single full image snapshot of the virtual machine and one or moreincrementals derived from the single full image snapshot. The singlefull image snapshot of the virtual machine may be stored using a firststorage device of a first type (e.g., a HDD) and the one or moreincrementals derived from the single full image snapshot may be storedusing a second storage device of a second type (e.g., an SSD). In thiscase, only a single full image needs to be stored and each version ofthe virtual machine may be generated from the single full image or thesingle full image combined with a subset of the one or moreincrementals. Furthermore, each version of the virtual machine may begenerated by performing a sequential read from the first storage device(e.g., reading a single file from a HDD) to acquire the full image and,in parallel, performing one or more reads from the second storage device(e.g., performing fast random reads from an SSD) to acquire the one ormore incrementals.

The distributed job scheduler 108 may be used for scheduling backup jobsthat acquire and store virtual machine snapshots for one or more virtualmachines over time. The distributed job scheduler 108 may follow abackup schedule to back up an entire image of a virtual machine at aparticular point in time or one or more virtual disks associated withthe virtual machine at the particular point in time. In one example, thebackup schedule may specify that the virtual machine be backed up at asnapshot capture frequency, such as every two hours or every 24 hours.Each backup job may be associated with one or more tasks to be performedin a sequence. Each of the one or more tasks associated with a job maybe run on a particular node within a cluster. In some cases, thedistributed job scheduler 108 may schedule a specific job to be run on aparticular node based on data stored on the particular node. Forexample, the distributed job scheduler 108 may schedule a virtualmachine snapshot job to be run on a node in a cluster that is used tostore snapshots of the virtual machine in order to reduce networkcongestion.

The distributed job scheduler 108 may comprise a distributedfault-tolerant job scheduler, in which jobs affected by node failuresare recovered and rescheduled to be run on available nodes. In oneembodiment, the distributed job scheduler 108 may be fully decentralizedand implemented without the existence of a master node. The distributedjob scheduler 108 may run job scheduling processes on each node in acluster or on a plurality of nodes in the cluster. In one example, thedistributed job scheduler 108 may run a first set of job schedulingprocesses on a first node in the cluster, a second set of job schedulingprocesses on a second node in the cluster, and a third set of jobscheduling processes on a third node in the cluster. The first set ofjob scheduling processes, the second set of job scheduling processes,and the third set of job scheduling processes may store informationregarding jobs, schedules, and the states of jobs using a metadatastore, such as distributed metadata store 110. In the event that thefirst node running the first set of job scheduling processes fails(e.g., due to a network failure or a physical machine failure), thestates of the jobs managed by the first set of job scheduling processesmay fail to be updated within a threshold period of time (e.g., a jobmay fail to be completed within 30 seconds or within minutes from beingstarted). In response to detecting jobs that have failed to be updatedwithin the threshold period of time, the distributed job scheduler 108may undo and restart the failed jobs on available nodes within thecluster.

The job scheduling processes running on at least a plurality of nodes ina cluster (e.g., on each available node in the cluster) may manage thescheduling and execution of a plurality of jobs. The job schedulingprocesses may include run processes for running jobs, cleanup processesfor cleaning up failed tasks, and rollback processes for rolling-back orundoing any actions or tasks performed by failed jobs. In oneembodiment, the job scheduling processes may detect that a particulartask for a particular job has failed and in response may perform acleanup process to clean up or remove the effects of the particular taskand then perform a rollback process that processes one or more completedtasks for the particular job in reverse order to undo the effects of theone or more completed tasks. Once the particular job with the failedtask has been undone, the job scheduling processes may restart theparticular job on an available node in the cluster.

The distributed job scheduler 108 may manage a job in which a series oftasks associated with the job are to be performed atomically (i.e.,partial execution of the series of tasks is not permitted). If theseries of tasks cannot be completely executed or there is any failurethat occurs to one of the series of tasks during execution (e.g., a harddisk associated with a physical machine fails or a network connection tothe physical machine fails), then the state of a data management systemmay be returned to a state as if none of the series of tasks were everperformed. The series of tasks may correspond with an ordering of tasksfor the series of tasks and the distributed job scheduler 108 may ensurethat each task of the series of tasks is executed based on the orderingof tasks. Tasks that do not have dependencies with each other may beexecuted in parallel.

In some cases, the distributed job scheduler 108 may schedule each taskof a series of tasks to be performed on a specific node in a cluster. Inother cases, the distributed job scheduler 108 may schedule a first taskof the series of tasks to be performed on a first node in a cluster anda second task of the series of tasks to be performed on a second node inthe cluster. In these cases, the first task may have to operate on afirst set of data (e.g., a first file stored in a file system) stored onthe first node and the second task may have to operate on a second setof data (e.g., metadata related to the first file that is stored in adatabase) stored on the second node. In some embodiments, one or moretasks associated with a job may have an affinity to a specific node in acluster.

In one example, if the one or more tasks require access to a databasethat has been replicated on three nodes in a cluster, then the one ormore tasks may be executed on one of the three nodes. In anotherexample, if the one or more tasks require access to multiple chunks ofdata associated with a virtual disk that has been replicated over fournodes in a cluster, then the one or more tasks may be executed on one ofthe four nodes. Thus, the distributed job scheduler 108 may assign oneor more tasks associated with a job to be executed on a particular nodein a cluster based on the location of data required to be accessed bythe one or more tasks.

In one embodiment, the distributed job scheduler 108 may manage a firstjob associated with capturing and storing a snapshot of a virtualmachine periodically (e.g., every 30 minutes). The first job may includeone or more tasks, such as communicating with a virtualizedinfrastructure manager, such as the virtualized infrastructure manager199 in FIG. 1B, to create a frozen copy of the virtual machine and totransfer one or more chunks (or one or more files) associated with thefrozen copy to a storage appliance, such as storage appliance 170 inFIG. 1A. The one or more tasks may also include generating metadata forthe one or more chunks, storing the metadata using the distributedmetadata store 110, storing the one or more chunks within thedistributed file system 112, and communicating with the virtualizedinfrastructure manager 199 that the frozen copy of the virtual machinemay be unfrozen or released from a frozen state. The metadata for afirst chunk of the one or more chunks may include information specifyinga version of the virtual machine associated with the frozen copy, a timeassociated with the version (e.g., the snapshot of the virtual machinewas taken at 5:30 p.m. on Jun. 29, 2018), and a file path to where thefirst chunk is stored within the distributed file system 112 (e.g., thefirst chunk is located at /snapshotsNM_B/s1/s1.chunk1). The one or moretasks may also include deduplication, compression (e.g., using alossless data compression algorithm such as LZ4 or LZ77), decompression,encryption (e.g., using a symmetric key algorithm such as Triple DES orAES-256), and decryption-related tasks.

The virtualization interface 104 may provide an interface forcommunicating with a virtualized infrastructure manager managing avirtualization infrastructure, such as virtualized infrastructuremanager 199 in FIG. 1B, and requesting data associated with virtualmachine snapshots from the virtualization infrastructure. Thevirtualization interface 104 may communicate with the virtualizedinfrastructure manager using an API for accessing the virtualizedinfrastructure manager (e.g., to communicate a request for a snapshot ofa virtual machine). In this case, storage appliance 170 may request andreceive data from a virtualized infrastructure without requiring agentsoftware to be installed or running on virtual machines within thevirtualized infrastructure. The virtualization interface 104 may requestdata associated with virtual blocks stored on a virtual disk of thevirtual machine that have changed since a last snapshot of the virtualmachine was taken or since a specified prior point in time. Therefore,in some cases, if a snapshot of a virtual machine is the first snapshottaken of the virtual machine, then a full image of the virtual machinemay be transferred to the storage appliance. However, if the snapshot ofthe virtual machine is not the first snapshot taken of the virtualmachine, then only the data blocks of the virtual machine that havechanged since a prior snapshot was taken may be transferred to thestorage appliance.

The virtual machine search index 106 may include a list of files thathave been stored using a virtual machine and a version history for eachof the files in the list. Each version of a file may be mapped to theearliest point-in-time snapshot of the virtual machine that includes theversion of the file or to a snapshot of the virtual machine thatincludes the version of the file (e.g., the latest point-in-timesnapshot of the virtual machine that includes the version of the file).In one example, the virtual machine search index 106 may be used toidentify a version of the virtual machine that includes a particularversion of a file (e.g., a particular version of a database, aspreadsheet, or a word processing document). In some cases, each of thevirtual machines that are backed up or protected using storage appliance170 may have a corresponding virtual machine search index.

In one embodiment, as each snapshot of a virtual machine is ingested,each virtual disk associated with the virtual machine is parsed in orderto identify a file system type associated with the virtual disk and toextract metadata (e.g., file system metadata) for each file stored onthe virtual disk. The metadata may include information for locating andretrieving each file from the virtual disk. The metadata may alsoinclude a name of a file, the size of the file, the last time at whichthe file was modified, and a content checksum for the file. Each filethat has been added, deleted, or modified since a previous snapshot wascaptured may be determined using the meta.da.ta (e.g., by comparing thetime at which a file was last modified with a time associated with theprevious snapshot). Thus, for every file that has existed within any ofthe snapshots of the virtual machine, a virtual machine search index maybe used to identify when the file was first created (e.g., correspondingwith a first version of the file) and at what times the file wasmodified (e.g., corresponding with subsequent versions of the file).Each version of the file may be mapped to a particular version of thevirtual machine that stores that version of the file.

In some cases, if a virtual machine includes a plurality of virtualdisks, then a virtual machine search index may be generated for eachvirtual disk of the plurality of virtual disks. For example, a firstvirtual machine search index may catalog and map files located on afirst virtual disk of the plurality of virtual disks and a secondvirtual machine search index may catalog and map files located on asecond virtual disk of the plurality of virtual disks. In this case, aglobal file catalog or a global virtual machine search index for thevirtual machine may include the first virtual machine search index andthe second virtual machine search index. A global file catalog may bestored for each virtual machine backed up by a storage appliance withina file system, such as distributed file system 112 in FIG. 1C.

The data management system 102 may comprise an application running onthe storage appliance (e.g., storage appliance 170) that manages andstores one or more snapshots of a virtual machine. In one example, thedata management system 102 may comprise a highest-level layer in anintegrated software stack running on the storage appliance. Theintegrated software stack may include the data management system 102,the virtualization interface 104, the distributed job scheduler 108, thedistributed metadata store 110, and the distributed file system 112.

In some cases, the integrated software stack may run on other computingdevices, such as a server or computing device 154 in FIG. 1A. The datamanagement system 102 may use the virtualization interface 104, thedistributed job scheduler 108, the distributed metadata store 110, andthe distributed file system 112 to manage and store one or moresnapshots of a virtual machine. Each snapshot of the virtual machine maycorrespond with a point-in-time version of the virtual machine. The datamanagement system 102 may generate and manage a list of versions for thevirtual machine. Each version of the virtual machine may map to orreference one or more chunks and/or one or more files stored within thedistributed file system 112. Combined together, the one or more chunksand/or the one or more files stored within the distributed file system112 may comprise a full image of the version of the virtual machine.

FIG. 2 shows an example virtualized infrastructure manager 199. In anembodiment, the manager 199 comprises a filter driver 230 and remainingcomponents reside on a different device, e.g., the storage device 156and/or the storage appliance 140, in which case, the filter driver 230transmits writes from the virtual machine to the other components. Theother components include a malware cataloger 210, a malware catalog 220,a detection engine 240, a timer 250, an optional bloom filter 260, anotifier 270 and virtual machine (VM) writes 280 that the filter driver230 transmits to the other components residing locally or at a differentdevice. In an embodiment, the filter driver 230 and the other componentscan reside on separate devices. For example, the filter driver mayreside on a server hosting the virtual machine and the remainingcomponents can be located on a separate device or a same device, but notpart of the actual virtual machine. In that way, writes to the VM andthe transmission of writes can be done asynchronously without effectingIO bursts to the VM. Further, the VM itself cannot be compromised bymalware (e.g., malware detection software disabled) as the malwaredetection is done outside of the VM.

The malware cataloger 210 generates a catalog from a set of knownmalware to store in the malware catalog 220. Four kilobyte alignedoffsets (binary and/or compressed binary) are fingerprinted. In anexample, fingerprinting can be done using a fingerprinting algorithmsuch as SHA (e.g., SHA256) and MD5 to efficiently find similarity withmalware binaries or other type of algorithm. Alternatively, other sizedoffsets may be used.

The filter driver 230 is per disk and transmits VM writes 280 to thedetection engine 240. The VM writes are also four kilobytes in length orother length to match the length of fingerprinted binaries in thecatalog 220. The detection engine 240 then computes the fingerprint forevery incoming four kilobyte aligned block. If the computed fingerprintmatches a fingerprint of any of the known malwares, the computedfingerprint for the write is a candidate for a match. The set offingerprints matched for a malware along with their counts is kept trackof. In an embodiment, the detection engine 240 can comprise a neuralnetwork trained using machine learning to recognize malware using atraining set of known malware. The detection engine 240 could thendetect malware without using the malware catalog and/or recognizemalware not yet cataloged.

If no matching fingerprint for a candidate is found for the last kminutes as counted by the timer 250, the detection engine 240 discardsthe candidate. If more than p % of the fingerprints of a malware havematched over a predetermined time (e.g., 50% over 60 minutes), then themalware has potentially been detected. In an embodiment, the bloomfilter 260 can match computed fingerprints against a bloom filter toreduce the number of fingerprints to check against known malware.

In addition to or alternatively, an embodiment can use offsets where thefingerprint occurs to increase the confidence of a match. That is,finding a malware's fingerprint subsequence in the fingerprints of theVM's writes.

Once malware is detected, the notifier 270 can power off affected VMs,send a notification to a user, and/or restore a VM to a point before themalware was detected. Accordingly, embodiments enable detection ofmalware in real-time during the download process to a VM before themalware is installed.

To ensure there is no impact to the primary VM during IO bursts, thefingerprint analysis can be done asynchronously while letting theinput/output go through. In case a match is detected, there is a log ofall the writes that were done, so they can be replayed to revert the VMto the state before the malware was downloaded.

In a multi-disk environment (e.g., RAID configurations), the detectionengine 240 can combine fingerprints computed from multiple diskstogether to identify malware.

FIG. 3 shows an example method 300 for protecting a virtual machine frommalware. The method 300 may be performed by the server 160 and/or at thestorage appliance 140 and/or storage appliance 170. For example, thefilter driver 230 may transmit copies of virtual machine writes to adevice not hosting the virtual machine. Alternatively, the method 300can be performed on the same device hosting the virtual machine butoutside of the virtual machine. Then, the method 300 can be performedseparately from the virtual machine without disrupting virtual machineoperation during input/output bursts.

Initially, the malware cataloger 210 generates (310) the malware catalog220 as discussed above in conjunction with the FIG. 2. Then, the filterdriver 230 transmits (315) a write received at the VM to outside of theVM to the detection engine 240. Next, the detection engine 240 computes(320) a fingerprint for each incoming write 280 to the VM. If (330)there is no match, then the detection engine 240 computes (320) afingerprint for the next incoming transmitted (315) write 280 to the VM.In an embodiment, the detection engine 240 operates asynchronously withrespect to the virtual machine. For example, the virtual machine cancontinue to receive input/output during the operation of method 300. If(330) there is a match, then the timer 250 increases (340) a counter. If(350) the counter is less than a threshold (e.g., less than 50% ofincoming writes over a predetermined time), then the detection engine240 returns to transmitting (315). Otherwise, if (350) the counter isgreater than a threshold, the notifier 270 takes action (360), such asstopping (disabling or powering off) the VM, notifying a user via email,pop-up, text message, recorded voice call, etc., blocking source addressof the malware, and/or reverting the VM to a pre-malware stage asdiscussed in conjunction with FIGS. 4 and 5 by reverting to a priorversion of the VM using a snapshot. In addition, optionally, the bloomfilter 260 can be used to expedite malware detection. Alternatively, orin addition, the detection engine 240 may comprise a neural networkusing machine learning to analyze the fingerprints to recognize malwarewithout the need to access the catalog. In an embodiment, if a counterbreaches a threshold then action (360) is taken.

FIG. 4 illustrates an example of a workload management system (WMS) 400.In one embodiment, the workload management system 400 may manage theextraction and storage of virtual machine snapshots captured atdifferent time points of one or more virtual machines running in thevirtualization manager 169 within the local datacenter 150. In oneembodiment, the workload management system 400 may manage the snapshotcapturing schedule of one or more virtual machines running on one ormore cloud servers. In one embodiment, the workload management system400 may manage the extraction and storage of virtual machine snapshotscaptured at different time points of one or more virtual machinesrunning in the virtualization manager 169 within the local datacenter150 and the snapshot capturing schedule of one or more virtual machinesrunning on one or more cloud servers. In response to a restore orrecover command from a WMS client, the workload management system 400may restore a point-in-time version of a virtual machine or restorepoint-in-time versions of one or more files located on the virtualmachine.

Referring to FIG. 4, the workload management system 400 may have severalsoftware-level components. The software-level components of the workloadmanagement system 400 may include a cloud snapshot metadata manager 442,an SLA policy engine 452, a data management system 454, a distributedjob scheduler 456, a distributed metadata store 460, and a distributedfile system 458. In one embodiment, the software-level components of theworkload management system 400 may he run using a dedicatedhardware-based appliance with one or more processors and memory system.In another embodiment, the software-level components of the workloadmanagement system 400 may he run from the cloud (e.g., thesoftware-level components may be installed on a cloud server'splatform).

The SLA policy engine 452 includes intelligence to determine thesnapshot capturing schedule to meet terms of service level agreementsbetween the workload management system 400 and the users, with specificaspects of the service, including how often to take virtual machinesnapshots and how long to keep the snapshots, as agreed between theworkload management system 400 and the users.

The distributed file system 458 may present itself as a single filesystem in the workload management system 400 and is shared by one ormore physical machines connected to the workload management system 400.Each file stored in the distributed file system 458 may be partitionedinto one or more chunks. Each of the one or more chunks may be storedwithin the distributed file system 458 as a separate file. The filesstored within the distributed file system 458 may be replicated ormirrored over a plurality of physical machines, thereby creating aload-balanced and fault-tolerant distributed file system. In oneexample, workload management system 400 may include ten physicalmachines and a first file corresponding with a snapshot of a virtualmachine (e.g.,/snapshots_A/s1/s1.full) may be replicated and stored onthree of the ten machines.

The distributed metadata store 460 may include a distributed databasemanagement system that provides high availability without a single pointof failure. In one embodiment, the distributed metadata store 460 maycomprise a database, such as a distributed document-oriented database.The distributed metadata store 460 may be used as a distributedkey-value storage system. In one example, the distributed metadata store460 may comprise a distributed NoSQL key-value store database. In somecases, the distributed metadata store 460 may include a partitioned rowstore, in which rows are organized into tables or other collections ofrelated data held within a structured format within the key-value storedatabase. A table (or a set of tables) may be used to store metadatainformation associated with one or more files stored within thedistributed file system 458. In one embodiment, a new file correspondingwith a snapshot of a virtual machine may be stored within thedistributed file system 458 and metadata associated with the new filemay be stored within the distributed metadata store 460.

In some cases, the distributed rnetadata store 460 may be used to manageone or more versions of a virtual machine. Each version of the virtualmachine may correspond with a full image snapshot of the virtual machinestored within the distributed file system 458 or an incremental snapshotof the virtual machine e.g., a forward incremental or reverseincremental) stored within the distributed file system 458. In oneembodiment, the one or more versions of the virtual machine maycorrespond to a plurality of files. The plurality of files may include asingle full image snapshot of the virtual machine and one or moreincrementals derived from the single full image snapshot. The singlefull image snapshot of the virtual machine may be stored using a firststorage device of a first type (e.g., an HDD) and the one or moreincrementals derived from the single full image snapshot may be storedusing a second storage device of a second type (e.g., an SSD). In thiscase, only a single full image needs to be stored, and each version ofthe virtual machine may be generated from the single full image or thesingle full image combined with a subset of the one or moreincrementals. Furthermore, each version of the virtual machine may begenerated by performing a sequential read from the first storage device(e.g., reading a single file from a HDD) to acquire the full image and,in parallel, performing one or more reads from the second storage device(e.g., performing fast random reads from an SSD) to acquire the one ormore incrementals.

The distributed job scheduler 456 may be used for scheduling backup jobsthat acquire and store virtual machine snapshots for one or more virtualmachines in the local datacenters and the cloud servers over time. Thedistributed job scheduler 456 may follow a backup schedule to back up anentire image of a virtual machine at a particular point in time or oneor more data volumes associated with the virtual machine at theparticular point in time. In one example, the backup schedule is the SLAagreement that prevails between the workload management system 400 andthe users. Each of the one or more tasks associated with a job may berun on a particular processor of the workload management system 400.

The distributed job scheduler 456 may comprise a distributed faulttolerant job scheduler, in which jobs affected by processor failures arerecovered and rescheduled to be run on available processors. Thedistributed job scheduler 456 may run job scheduling processes on eachprocessor in a workload management system 400 or on a plurality ofprocessors in the workload management system 400. In one example, thedistributed job scheduler 456 may run a first set of job schedulingprocesses on a first processor in the workload management system 400, asecond set of job scheduling processes on a second processor in theworkload management system 400, and a third set of job schedulingprocesses on a third processor in the workload management system 400.The first set of job scheduling processes, the second set of jobscheduling processes, and the third set of job scheduling processes maystore information regarding jobs, schedules, and the states of jobsusing a metadata store, such as distributed metadata store 460. In theevent that the first processor running the first set of job schedulingprocesses fails (e.g., due to a network failure or a physical machinefailure), the states of the jobs managed by the first set of jobscheduling processes may fail to be updated within a threshold period oftime (e.g., a job may fail to be completed within 30 seconds or within 3minutes from being started). In response to detecting jobs that havefailed to be updated within the threshold period of time, thedistributed job scheduler 456 may undo and restart the failed jobs onavailable processors within the workload management system 400.

The cloud snapshot metadata manager 442 may have the capability tofinding content in snapshots captured from virtual machines running onmultiple cloud servers, compile a metadata file for the contents in thesnapshots and forward the metadata file to the WMS clients. The cloudsnapshot metadata manager 442 may request data associated with virtualblocks stored on a data volumes of the virtual machine that have changedsince a last snapshot of the virtual machine was taken or since aspecified prior point in time. Therefore, in some cases, if a snapshotof a virtual machine is the first snapshot taken of the virtual machine,then a full image of the virtual machine may he compiled to make ametadata file. However, if the snapshot of the virtual machine is notthe first snapshot taken of the virtual machine, then only the datablocks of the virtual machine that have changed since a prior snapshotwas taken may be compiled to make a metadata file.

The data management system 454 may comprise an application running onthe workload management system 400 that manages and stores one or moresnapshots of a virtual machine in the local datacenter 150. In oneexample, the data management system 454 may comprise a highest levellayer in an integrated software stack running on the workload managementsystem 400. The integrated software stack may include the datamanagement system 454, the distributed job scheduler 456, thedistributed metadata store 460, and the distributed file system 458. Insome cases, the integrated software stack may run on other computingdevices, such as a server or computing device. The local workloadmanagement system 400 may use the distributed job scheduler 456, thedistributed metadata store 460, and the distributed file system 458 tomanage and store one or more snapshots of a virtual machine in the localdatacenter. Each snapshot of the virtual machine may correspond to apoint-in-time version of the virtual machine. The local workloadmanagement system 400 may generate and manage a list of versions for thevirtual machine. Each version of the virtual machine may map to orreference one or more chunks and/or one or more files stored within thedistributed file system 458. Combined together, the one or more chunksand/or the one or more files stored within the distributed file system458 may comprise a full image of the version of the virtual machine.

FIG. 5 is an example workflow 1500 illustrating a representative methodof restoring a virtual machine on the cloud server A 505 by the workloadmanagement system 400. In some embodiments, the actions in the workflowmay be performed in different orders and with different, fewer oradditional actions than those illustrated in FIG. 5. Multiple actionscan be combined in some implementations.

FIG. 5 includes workflow 1500 that begins at S15.1 when a clientrequests, through the virtual machine search index 106, to restore thevirtual machine X on a cloud server A 505. The request is sent to thecloud snapshot metadata manager 442 in the workload management system400.

Workflow 1500 continues at S15.2 when the cloud snapshot metadatamanager 442 instantiates a recovery virtual machine 1502 on the cloudserver A 505.

At S15.3, the recovery virtual machine 1502 mounts a snapshot of thevirtual machine X into its own data volumes. In one embodiment, themounted snapshot may be selected by the user. In another embodiment, themounted snapshot may be the last saved snapshot. In one embodiment, themounted snapshot may contain data for the corrupted data volumes. Inanother embodiment, the mounted snapshot may contain data for all thedata volumes.

At SI5.4, the recovery virtual machine 1502 shuts down the virtualmachine X.

At SI5.5, the recovery virtual machine 1502 detaches the damaged datavolumes from the virtual machine X. In one embodiment, the recoveryvirtual machine 1502 may detach one or more corrupted data volumes,while keeping the uncorrupted volumes intact. In another embodiment, therecovery virtual machine 1502 may detach all the data volumes.

At S15.6, the recovery virtual machine 1502 detaches its own datavolumes and attaches the detached data volumes to the virtual machine X.In one embodiment, the recovery virtual machine 1502 may also create anew root volume for the virtual machine X. In one embodiment, a rootvolume is created from an operating system image. In another embodiment,a root volume is created by mounting a snapshot containing an image of aprevious version of a root volume of the virtual machine X. In oneembodiment, data volumes which were mounted from snapshots are restored,while the rest of the data volumes of the virtual machine remain intact.In one embodiment, both the corrupted data volumes and the uncorrupteddata volumes are restored.

At SI5.7, the recovery virtual machine 1502 starts the virtual machine Xwith restored data volumes and root volume.

FIG. 6 is a block diagram illustrating an example software architecture606, which may he used in conjunction with various hardwarearchitectures herein described. FIG. 6 is a non-limiting example of asoftware architecture, and it will be appreciated that many otherarchitectures may be implemented to facilitate the functionalitydescribed herein. The software architecture 606 may execute on hardwaresuch as a machine 700 of FIG. 7 that includes, among other things,processors, memory, and I/O components. A representative hardware layer652 is illustrated and can represent, for example, the machine 700 ofFIG. 7. The representative hardware layer 652 includes a processing unit654 having associated executable instructions 604. The executableinstructions 604 represent the executable instructions of the softwarearchitecture 606, including implementation of the methods, components,and so forth described herein. The hardware layer 652 also includes amemory/storage 656, which also has the executable instructions 604. Thehardware layer 652 may also comprise other hardware 658.

In the example architecture of FIG. 6, the software architecture 606 maybe conceptualized as a stack of layers where each layer providesparticular functionality. For example, the software architecture 606 mayinclude layers such as an operating system 602, libraries 620,frameworks/middleware 618, applications 616, and a presentation layer614. Operationally, the applications 616 and/or other components withinthe layers may invoke API calls 608 through the software stack andreceive a response in the form of messages 612. The layers illustratedare representative in nature and not all software architectures have alllayers. For example, some mobile or special-purpose operating systemsmay not provide a frameworks/middleware 618, while others may providesuch a layer. Other software architectures may include additional ordifferent layers.

The operating system 602 may manage hardware resources and providecommon services. The operating system 602 may include, for example, akernel 622, services 624, and drivers 626. The kernel 622 may act as anabstraction layer between the hardware and the other software layers.For example, the kernel 622 may be responsible for memory management,processor management (e.g., scheduling), component management,networking, security settings, and so on. The services 624 may provideother common services for the other software layers. The drivers 626 areresponsible for controlling or interfacing with the underlying hardware.For instance, the drivers 626 include display drivers, camera drivers,Bluetooth® drivers, flash memory drivers, serial communication drivers(e.g., Universal Serial Bus (USB) drivers), Wi-Fi® drivers, audiodrivers, power management drivers, and so forth depending on thehardware configuration.

The libraries 620 provide a common infrastructure that is used by theapplications 616 and/or other components and/or layers. The libraries620 provide functionality that allows other software components toperform tasks in an easier fashion than by interfacing directly with theunderlying operating system 602 functionality (e.g., kernel 622,services 624, and/or drivers 626). The libraries 620 may include systemlibraries 644 (e.g., C standard library) that may provide functions suchas memory allocation functions, string manipulation functions,mathematical functions, and the like. In addition, the libraries 620 mayinclude API libraries 646 such as media libraries (e.g., libraries tosupport presentation and manipulation of various media formats such asMPEG4, H.264, MP3, AAC, AMR, JPG, or PNG), graphics libraries (e.g., anOpenGL framework that may be used to render 2D and 3D graphic content ona display), database libraries (e.g., SQLite that may provide variousrelational database functions), web libraries (e.g., WebKit that mayprovide web browsing functionality), and the like. The libraries 620 mayalso include a wide variety of other libraries 648 to provide many otherAPIs to the applications 616 and other software components/modules.

The frameworks/middleware 618 provide a higher-level commoninfrastructure that may be used by the applications 616 and/or othersoftware components/modules. For example, the frameworks/middleware 618may provide various graphic user interface (GUI) functions, high-levelresource management, high-level location services, and so forth. Theframeworks/middleware 618 may provide a broad spectrum of other APIsthat may be utilized by the applications 616 and/or other softwarecomponents/modules, some of which may be specific to a particularoperating system 602 or platform.

The applications 616 include built-in applications 638 and/orthird-party applications 640. Examples of representative built-inapplications 638 may include, but are not limited to, a contactsapplication, a browser application, a book reader application, alocation application, a media application, a messaging application,and/or a game application. The third-party applications 640 may includean application developed using the ANDROID™ or IOS™ software developmentkit (SDK) by an entity other than the vendor of the particular platform,and may be mobile software running on a mobile operating system such asIOS™, ANDROID™, WINDOWS® Phone, or other mobile operating systems. Thethird-party applications 640 may invoke the API calls 608 provided bythe mobile operating system (such as the operating system 602) tofacilitate functionality described herein.

The applications 616 may use built-in operating system functions (e.g.,kernel 622, services 624, and/or drivers 626), libraries 620, andframeworks/middleware 618 to create user interfaces to interact withusers of the system. Alternatively, or additionally, in some systems,interactions with a user may occur through a presentation layer, such asthe presentation layer 614. In these systems, the application/component“logic” can be separated from the aspects of the application/componentthat interact with a user.

FIG. 7 is a block diagram illustrating components of a machine 700,according to some example embodiments, able to read instructions from amachine-readable medium (e.g., a machine-readable storage medium) andperform any one or more of the methodologies discussed herein.Specifically, FIG. 7 shows a diagrammatic representation of the machine700 in the example form of a computer system, within which instructions716 (e.g., software, a program, an application, an applet, an app, orother executable code) for causing the machine 700 to perform any one ormore of the methodologies discussed herein may be executed. As such, theinstructions 716 may be used to implement modules or componentsdescribed herein. The instructions 716 transform the general,non-programmed machine 700 into a particular machine 700 programmed tocarry out the described and illustrated functions in the mannerdescribed. In alternative embodiments, the machine 700 operates as astandalone device or may be coupled (e.g., networked) to other machines.In a networked deployment, the machine 700 may operate in the capacityof a server machine or a client machine in a server-client networkenvironment, or as a peer machine in a peer-to-peer (or distributed)network environment. The machine 700 may comprise, but not be limitedto, a server computer, a client computer, a personal computer (PC), atablet computer, a laptop computer, a netbook, a set-top box (STB), apersonal digital assistant (PDA), an entertainment media system, acellular telephone, a smartphone, a mobile device, a wearable device(e.g., a smart watch), a smart home device (e.g., a smart appliance),other smart devices, a web appliance, a network router, a networkswitch, a network bridge, or any machine capable of executing theinstructions 716, sequentially or otherwise, that specify actions to betaken by the machine 700. Further, while only a single machine 700 isillustrated, the term “machine” shall also be taken to include acollection of machines that individually or jointly execute theinstructions 716 to perform any one or more of the methodologiesdiscussed herein.

The machine 700 may include processors 710, memory/storage 730, and I/Ocomponents 750, which may be configured to communicate with each othersuch as via a bus 702. The memory/storage 730 may include a main memory732, static memory 734, and a storage unit 736, both accessible to theprocessors 710 such as via the bus 702. The storage unit 736 and mainmemory 732 store the instructions 716 embodying any one or more of themethodologies or functions described herein. The instructions 716 mayalso reside, completely or partially, within the static memory 734,within the storage unit 736 (e.g., on machine readable-medium 738),within at least one of the processors 710 (e.g., within the processorcache memory accessible to processors 712 or 714), or any suitablecombination thereof, during execution thereof by the machine 700.Accordingly, the main memory 732, static memory 734, the storage unit736, and the memory of the processors 710 are examples ofmachine-readable media.

The I/O components 750 may include a wide variety of components toreceive input, provide output, produce output, transmit information,exchange information, capture measurements, and so on. The specific I/Ocomponents 750 that are included in a particular machine 700 will dependon the type of machine. For example, portable machines such as mobilephones will likely include a touch input device or other such inputmechanisms, while a headless server machine will likely not include sucha touch input device. It will be appreciated that the I/O components 750may include many other components that are not shown in FIG. 7. The I/Ocomponents 750 are grouped according to functionality merely forsimplifying the following discussion and the grouping is in no waylimiting. In various example embodiments, the I/O components 750 mayinclude output components 752 and input components 754. The outputcomponents 752 may include visual components (e.g., a display such as aplasma display panel (PDP), a light-emitting diode (LED) display, aliquid-crystal display (LCD), a projector, or a cathode ray tube (CRT)),acoustic components (e.g., speakers), haptic components (e.g., avibratory motor, resistance mechanisms), other signal generators, and soforth. The input components 754 may include alphanumeric inputcomponents (e.g., a keyboard, a touch screen configured to receivealphanumeric input, a photo-optical keyboard, or other alphanumericinput components), point-based input components (e.g., a mouse, atouchpad, a trackball, a joystick, a motion sensor, or other pointinginstruments), tactile input components (e.g., a physical button, a touchscreen that provides location and/or force of touches or touch gestures,or other tactile input components), audio input components (e.g., amicrophone), and the like.

In further example embodiments, the I/O components 750 may includebiometric components 756, motion components 758, environment components760, or position components 762 among a wide array of other components.For example, the biometric components 756 may include components todetect expressions (e.g., hand expressions, facial expressions, vocalexpressions, body gestures, or eye tracking), measure biosignals (e.g.,blood pressure, heart rate, body temperature, perspiration, or brainwaves), identify a person (e.g., voice identification, retinalidentification, facial identification, fingerprint identification, orelectroencephalogram-based identification), and the like. The motioncomponents 758 may include acceleration sensor components (e.g.,accelerometer), gravitation sensor components, rotation sensorcomponents (e.g., gyroscope), and so forth. The environment components760 may include, for example, illumination sensor components (e.g.,photometer), temperature sensor components (e.g., one or morethermometers that detect ambient temperature), humidity sensorcomponents, pressure sensor components (e.g., barometer), acousticsensor components (e.g., one or more microphones that detect backgroundnoise), proximity sensor components (e.g., infrared sensors that detectnearby objects), or other components that may provide indications,measurements, or signals corresponding to a surrounding physicalenvironment. The position components 762 may include location sensorcomponents (e.g., a GPS receiver component), altitude sensor components(e.g., altimeters or barometers that detect air pressure from whichaltitude may be derived), orientation sensor components (e.g.,magnetometers), and the like.

Communication may be implemented using a wide variety of technologies.The I/O components 750 may include communication components 764 operableto couple the machine 700 to a network 780 or devices 770 via a coupling782 and a coupling 772, respectively. For example, the communicationcomponents 764 may include a network interface component or othersuitable device to interface with the network 780. In further examples,the communication components 764 may include wired communicationcomponents, wireless communication components, cellular communicationcomponents, near field communication (NFC) components, Bluetooth®components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and othercommunication components to provide communication via other modalities.The devices 770 may be another machine or any of a wide variety ofperipheral devices (e.g., a peripheral device coupled via a USB).

Moreover, the communication components 764 may detect identifiers orinclude components operable to detect identifiers. For example, thecommunication components 764 may include radio frequency identification(RFID) tag reader components, NFC smart tag detection components,optical reader components (e.g., an optical sensor to detectone-dimensional barcodes such as Universal Product Code (UPC) barcode,multi-dimensional barcodes such as Quick Response (QR) code, Aztec code,Data Matrix, Dataglyph, MaxiCode, PDF418, Ultra Code, UCC RSS-2Dbarcode, and other optical codes), or acoustic detection components(e.g., microphones to identify tagged audio signals). In addition, avariety of information may be derived via the communication components764, such as location via Internet Protocol (IP) geolocation, locationvia Wi-Fi® signal triangulation, location via detecting an NFC beaconsignal that may indicate a particular location, and so forth.

“CARRIER SIGNAL” in this context refers to any intangible medium that iscapable of storing, encoding, or carrying instructions 716 for executionby the machine 700, and includes digital or analog communicationssignals or other intangible media to facilitate communication of suchinstructions 716. Instructions 716 may be transmitted or received overthe network 780 using a transmission medium via a network interfacedevice and using any one of a number of well-known transfer protocols.

“CLIENT DEVICE” in this context refers to any machine 700 thatinterfaces to a network 780 to obtain resources from one or more serversystems or other client devices. A client device may be, but is notlimited to, a mobile phone, desktop computer, laptop, PDA, smartphone,tablet, ultrabook, netbook, multi-processor system, microprocessor-basedor programmable consumer electronics system, game console, set-top box,or any other communication device that a user may use to access anetwork 780.

“COMMUNICATIONS NETWORK” in this context refers to one or more portionsof a network 780 that may be an ad hoc network, an intranet, anextranet, a virtual private network (VPN), a local area network (LAN), awireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), ametropolitan area network (MAN), the Internet, a portion of theInternet, a portion of the Public Switched Telephone Network (PSTN), aplain old telephone service (POTS) network, a cellular telephonenetwork, a wireless network, a Wi-Fi® network, another type of network,or a combination of two or more such networks. For example, a network ora portion of a network 780 may include a wireless or cellular networkand the coupling 782 may be a Code Division Multiple Access (CDMA)connection, a Global System for Mobile communications (GSM) connection,or another type of cellular or wireless coupling. In this example, thecoupling may implement any of a variety of types of data transfertechnology, such as Single Carrier Radio Transmission Technology(1×RTT), Evolution-Data Optimized (EVDO) technology, General PacketRadio Service (GPRS) technology, Enhanced Data rates for GSM Evolution(EDGE) technology, third Generation Partnership Project (3GPP) including3G, fourth generation wireless (4G) networks, Universal MobileTelecommunications System (UMTS), High-Speed Packet Access (HSPA),Worldwide Interoperability for Microwave Access (WiMAX), Long-TermEvolution (LTE) standard, others defined by various standard-settingorganizations, other long-range protocols, or other data transfertechnology.

“MACHINE-READABLE MEDIUM” in this context refers to a component, adevice, or other tangible media able to store instructions 716 and datatemporarily or permanently and may include, but is not limited to,random-access memory (RAM), read-only memory (ROM), buffer memory, flashmemory, optical media, magnetic media, cache memory, other types ofstorage (e.g., erasable programmable read-only memory (EPROM)), and/orany suitable combination thereof. The term “machine-readable medium”should be taken to include a single medium or multiple media (e.g., acentralized or distributed database, or associated caches and servers)able to store instructions 716. The term “machine-readable medium” shallalso be taken to include any medium, or combination of multiple media,that is capable of storing instructions 716 (e.g., code) for executionby a machine 700, such that the instructions 716, when executed by oneor more processors 710 of the machine 700, cause the machine 700 toperform any one or more of the methodologies described herein.Accordingly, a “machine-readable medium” refers to a single storageapparatus or device, as well as “cloud-based” storage systems or storagenetworks that include multiple storage apparatus or devices. The term“machine-readable medium” excludes signals per se.

“COMPONENT” in this context refers to a device, a physical entity, orlogic having boundaries defined by function or subroutine calls, branchpoints, APIs, or other technologies that provide for the partitioning ormodularization of particular processing or control functions. Componentsmay be combined via their interfaces with other components to carry outa machine process. A component may be a packaged functional hardwareunit designed for use with other components and a part of a program thatusually performs a particular function of related functions. Componentsmay constitute either software components (e.g., code embodied on amachine-readable medium) or hardware components.

A “hardware component” is a tangible unit capable of performing certainoperations and may be configured or arranged in a certain physicalmanner. In various example embodiments, one or more computer systems(e.g., a standalone computer system, a client computer system, or aserver computer system) or one or more hardware components of a computersystem (e.g., a processor 712 or a group of processors 710) may beconfigured by software (e.g., an application or application portion) asa hardware component that operates to perform certain operations asdescribed herein. A hardware component may also be implementedmechanically, electronically, or any suitable combination thereof. Forexample, a hardware component may include dedicated circuitry or logicthat is permanently configured to perform certain operations. A hardwarecomponent may be a special-purpose processor, such as afield-programmable gate array (FPGA) or an application-specificintegrated circuit (ASIC). A hardware component may also includeprogrammable logic or circuitry that is temporarily configured bysoftware to perform certain operations. For example, a hardwarecomponent may include software executed by a general-purpose processoror other programmable processor. Once configured by such software,hardware components become specific machines (or specific components ofa machine 700) uniquely tailored to perform the configured functions andare no longer general-purpose processors 710.

It will be appreciated that the decision to implement a hardwarecomponent mechanically, in dedicated and permanently configuredcircuitry, or in temporarily configured circuitry (e.g., configured bysoftware) may be driven by cost and time considerations. Accordingly,the phrase “hardware component” (or “hardware-implemented component”)should be understood to encompass a tangible entity, be that an entitythat is physically constructed, permanently configured (e.g.,hardwired), or temporarily configured (e.g., programmed) to operate in acertain manner or to perform certain operations described herein.

Considering embodiments in which hardware components are temporarilyconfigured (e.g., programmed), each of the hardware components need notbe configured or instantiated at any one instance in time. For example,where a hardware component comprises a general-purpose processor 712configured by software to become a special-purpose processor, thegeneral-purpose processor 712 may be configured as respectivelydifferent special-purpose processors (e.g., comprising differenthardware components) at different times. Software accordingly configuresa particular processor 712 or processors 710, for example, to constitutea particular hardware component at one instance of time and toconstitute a different hardware component at a different instance oftime.

Hardware components can provide information to, and receive informationfrom, other hardware components. Accordingly, the described hardwarecomponents may be regarded as being communicatively coupled. Wheremultiple hardware components exist contemporaneously, communications maybe achieved through signal transmission (e.g., over appropriate circuitsand buses) between or among two or more of the hardware components. Inembodiments in which multiple hardware components are configured orinstantiated at different times, communications between or among suchhardware components may be achieved, for example, through the storageand retrieval of information in memory structures to which the multiplehardware components have access. For example, one hardware component mayperform an operation and store the output of that operation in a memorydevice to which it is communicatively coupled. A further hardwarecomponent may then, at a later time, access the memory device toretrieve and process the stored output. Hardware components may alsoinitiate communications with input or output devices, and can operate ona resource (e.g., a collection of information).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors 710 that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors 710 may constitute processor-implementedcomponents that operate to perform one or more operations or functionsdescribed herein. As used herein, “processor-implemented component”refers to a hardware component implemented using one or more processors710. Similarly, the methods described herein may be at least partiallyprocessor-implemented, with a particular processor 712 or processors 710being an example of hardware. For example, at least some of theoperations of a method may be performed by one or more processors 710 orprocessor-implemented components. Moreover, the one or more processors710 may also operate to support performance of the relevant operationsin a “cloud computing” environment or as a “software as a service”(SaaS). For example, at least some of the operations may be performed bya group of computers (as examples of machines 700 including processors710), with these operations being accessible via a network 780 (e.g.,the Internet) and via one or more appropriate interfaces (e.g., an API).The performance of certain of the operations may be distributed amongthe processors 710, not only residing within a single machine 700, butdeployed across a number of machines 700. In some example embodiments,the processors 710 or processor-implemented components may be located ina single geographic location e.g., within a home environment, an officeenvironment, or a server farm). In other example embodiments, theprocessors 710 or processor-implemented components may be distributedacross a number of geographic locations.

“PROCESSOR” in this context refers to any circuit or virtual circuit (aphysical circuit emulated by logic executing on an actual processor 712)that manipulates data values according to control signals (e.g.,“commands,” “op codes,” “machine code,” etc.) and which producescorresponding output signals that are applied to operate a machine 700.A processor may, for example, be a central processing unit (CPU), areduced instruction set computing (RISC) processor, a complexinstruction set computing (CISC) processor, a graphics processing unit(GPU), a digital signal processor (DSP), an ASIC, a radio-frequencyintegrated circuit (RFIC), or any combination thereof. A processor 710may further be a multi-core processor 710 having two or more independentprocessors 712, 714 (sometimes referred to as “cores”) that may executeinstructions 716 contemporaneously.

“TIMESTAMP” in this context refers to a sequence of characters orencoded information identifying when a certain event occurred, forexample giving date and time of day, sometimes accurate to a smallfraction of a second.

The following examples describe various embodiments of methods,machine-readable media, and systems (e.g., machines, devices, or otherapparatus) discussed herein.

EXAMPLES

1. A data management system, comprising:

-   a storage appliance configured to store a snapshot of a virtual    machine;-   one or more processors in communication with the storage appliance,    the one or more processors configured to perform operations    including:-   receiving, at the storage appliance from a server hosting the    virtual machine, a write made to the virtual machine;-   computing, at the storage appliance, a fingerprint of the    transmitted write;-   comparing, at the storage appliance, the computed fingerprint to    malware fingerprints in a malware catalog;-   repeating the computing and comparing; and-   disabling the virtual machine if a number of matches from the    comparing breaches a predetermined threshold over a predetermined    amount of time.

2. The system of example 1, wherein the operations further includerestoring the virtual machine using the snapshot stored in the storageappliance to a state before the predetermined threshold was breached.

3. The system of example 1, wherein the operations further includeblocking writes from a source of the matches.

4. The system of example 1, wherein the operations further includegenerating the malware catalog including generating fingerprints ofbinaries and compressed binaries of known malware.

5. The system of example 4, wherein the fingerprints are computed at 4kilobytes aligned offsets generated using SHA256.

6. The system of example 1, wherein the operations further includerepeatedly generating snapshots of the virtual machine over time.

7. A computer-implemented method at a data management system, the methodcomprising:

-   receiving, at a storage appliance from a server hosting a virtual    machine, a write made to the virtual machine;-   computing, at the storage appliance, a fingerprint of the    transmitted write;-   comparing, at the storage appliance, the computed fingerprint to    malware fingerprints in a malware catalog;-   repeating the computing and comparing; and-   disabling the virtual machine if a number of matches from the    comparing breaches a predetermined threshold over a predetermined    amount of time.

8. The method of example 7, further comprising restoring the virtualmachine using a snapshot stored in the storage appliance to a statebefore the predetermined threshold was breached.

9. The method of example 7, further comprising blocking writes from asource of the matches.

10. The method of example 7, further comprising generating the malwarecatalog including generating fingerprints of binaries and compressedbinaries of known malware.

11. The method of example 10, wherein the fingerprints are computed at 4kilobytes aligned offsets generated using SHA256.

12. The method of example 7, further comprising repeatedly generatingsnapshots of the virtual machine over time.

13. A non-transitory, machine-readable medium storing instructionswhich, when read by a storage appliance, cause the storage appliance toperform operations comprising, at least:

-   receiving, at the storage appliance from a server hosting a virtual    machine, a write made to the virtual machine;-   computing, at the storage appliance, a fingerprint of the    transmitted write;-   comparing, at the storage appliance, the computed fingerprint to    malware fingerprints in a malware catalog;-   repeating the computing and comparing; and-   disabling the virtual machine if a number of matches from the    comparing breaches a predetermined threshold over a predetermined    amount of time.

14. The machine-readable medium of example 13, wherein the operationsfurther include restoring the virtual machine using a snapshot stored inthe storage appliance to a state before the predetermined threshold wasbreached.

15. The machine-readable medium of example 13, wherein the operationsfurther include blocking writes from a source of malware.

16. The machine-readable medium of example 13, wherein the operationsfurther include generating the malware catalog including generatingfingerprints of binaries and compressed binaries of known malware.

17. The machine-readable medium of example 16, wherein the fingerprintsare computed at 4 kilobytes aligned offsets generated using SHA256.

18. The machine-readable medium of example 13, wherein the operationsfurther include repeatedly generating snapshots of the virtual machineover time.

1. A data management system, comprising: a storage appliance configuredto store a snapshot of a virtual machine; one or more processors incommunication with the storage appliance, the one or more processorsconfigured to perform operations including: receiving, at the storageappliance from a server hosting the virtual machine, a write made to thevirtual machine; computing, at the storage appliance, a fingerprint ofthe transmitted write; comparing, at the storage appliance, the computedfingerprint to malware fingerprints in a malware catalog; repeating thecomputing and comparing; and disabling the virtual machine if a numberof matches from the comparing breaches a predetermined threshold over apredetermined amount of time.
 2. The system of claim 1, wherein theoperations further include restoring the virtual machine using thesnapshot stored in the storage appliance to a state before thepredetermined threshold was breached.
 3. The system of claim 1, whereinthe operations further include blocking writes from a source of thematches.
 4. The system of claim 1, wherein the operations furtherinclude generating the malware catalog including generating fingerprintsof binaries and compressed binaries of known malware.
 5. The system ofclaim 4, wherein the fingerprints are computed at 4 kilobytes alignedoffsets generated using SHA256.
 6. The system of claim 1, wherein theoperations further include repeatedly generating snapshots of thevirtual machine over time.
 7. A computer-implemented method at a datamanagement system, the method comprising: receiving, at a storageappliance from a server hosting a virtual machine, a write made to thevirtual machine; computing, at the storage appliance, a fingerprint ofthe transmitted write; comparing, at the storage appliance, the computedfingerprint to malware fingerprints in a malware catalog; repeating thecomputing and comparing; and disabling the virtual machine if a numberof matches from the comparing breaches a predetermined threshold over apredetermined amount of time.
 8. The method of claim 7, furthercomprising restoring the virtual machine using a snapshot stored in thestorage appliance to a state before the predetermined threshold wasbreached.
 9. The method of claim 7, further comprising blocking writesfrom a source of the matches.
 10. The method of claim 7, furthercomprising generating the malware catalog including generatingfingerprints of binaries and compressed binaries of known malware. 11.The method of claim 10, wherein the fingerprints are computed at 4kilobytes aligned offsets generated using SHA256.
 12. The method ofclaim 7, further comprising repeatedly generating snapshots of thevirtual machine over time.
 13. A non-transitory, machine-readable mediumstoring instructions which, when read by a storage appliance, cause thestorage appliance to perform operations comprising, at least: receiving,at the storage appliance from a server hosting a virtual machine, awrite made to the virtual machine; computing, at the storage appliance,a fingerprint of the transmitted write; comparing, at the storageappliance, the computed fingerprint to malware fingerprints in a malwarecatalog; repeating the computing and comparing; and disabling thevirtual machine if a number of matches from the comparing breaches apredetermined threshold over a predetermined amount of time.
 14. Themachine-readable medium of claim 13, wherein the operations furtherinclude restoring the virtual machine using a snapshot stored in thestorage appliance to a state before the predetermined threshold wasbreached.
 15. The machine-readable medium of claim 13, wherein theoperations further include blocking writes from a source of the matches.16. The machine-readable medium of claim 13, wherein the operationsfurther include generating the malware catalog including generatingfingerprints of binaries and compressed binaries of known malware. 17.The machine-readable medium of claim 16, wherein the fingerprints arecomputed 4 kilobytes aligned offsets generated using SHA256.
 18. Themachine-readable medium of claim 13, wherein the operations furtherinclude repeatedly generating snapshots of the virtual machine overtime.